Abstract B14: Wnt signaling circuits in glioblastoma multiforme
Notice bibliographique
Résumé
Abstract Glioblastoma multiforme (GBM) is the most common malignant tumour in the central nervous system with a prevalence of 2-3 cases per 100 000 people. Although the standard treatment of surgery, chemotherapy and radiotherapy improve survival, the median survival continues to remain at only 15 months with a 5-year survival rate of under 10%. Glioma neural stem-like (GNS) cells have been identified in GBM and have the capability of regenerating the tumour. Treatment strategies that target the majority of the tumour may be incapable of also targeting GNS cells and thus characterization of GNS cells may provide insight into additional treatment options. The Wnt signalling pathway has been linked to several cancers including GBM. Wnt signalling involves the secretion of Wnt ligand proteins that bind to specific Frizzled (FZD) receptor complexes on the cell surface of Wnt-responding cells to activate intracellular signalling cascades. The transcriptional and epigenetic regulation in GNS cells is the focus of several recent studies. The transcription factor ASCL1 was identified to be overexpressed and to lead to Wnt signalling activation by repressing Dickkopf (DKK1, Wnt inhibitor). Using microarray data we analyzed the expression of FZD receptors and Wnt target genes in over 50 primary GNS cell lines cultured in serum free conditions in order to maintain the GIC population and identified a subgroup of glioma lines with activated Wnt signalling. To determine the requirement of autocrine Wnt signalling for GNS cell renewal we inhibited Wnt secretion, using the porcupine inhibitor LGK974, and measured self-renewal using a limited dilution assay. There was a significant reduction in GNS cell frequency with LGK974 (1uM) treatment in four out of eight lines tested (G432NS, G472NS, G511NS and G523NS). Furthermore, a secondary sphere assay with G523NS cells also showed a significant reduction in GNS cell frequency. When G511NS and G523NS cells were treated with LGK974 (1uM) over a two week period, there was a significant increase in the percentage of GFAP (astrocytic marker) expressing cells whereas a two week treatment with Bio (1uM, Wnt activator), significantly increased the percentage of Tuj1 (neuronal marker) expressing cells. This finding suggest that these cells require a specific amount of Wnt signalling for self-renewal and Wnt inhibition or activation may lead to differentiation. RNAseq analysis comparing the four LGK974 responsive lines with the four LGK974 unresponsive lines identified ASCL1 to be highly expressed in the responsive lines. Gene set enrichment analysis identified four gene sets significantly enriched in the responsive group including the Glioblastoma Proneural gene set whereas genes from the Glioblastoma Mesenchymal gene set were significantly enriched in the unresponsive group. We have identified a subset of GNS cells that are dependent on Wnt secretion for self-renewal and RNAseq analysis suggests that GBMs that fall under the Proneural subtype may be sensitive to Wnt inhibition. Citation Format: Nishani Rajakulendran, Hayden Selvadurai, Katherine Rowland, Nicole Park, Nizar Batada, Peter Dirks, Stephane Angers. Wnt signaling circuits in glioblastoma multiforme. [abstract]. In: Proceedings of the AACR Special Conference: Developmental Biology and Cancer; Nov 30-Dec 3, 2015; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(4_Suppl):Abstract nr B14.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».